Swirl Search

Swirl answers a question by searching your applications live, ranking what comes back and returning an answer with sources you can click through. The premise is that most AI search products ask you to copy everything into a vector database first and then govern that copy forever, and that this step can be skipped.

Queries run against each source with the user's own permissions, so access control is enforced where it already lives rather than rebuilt in a second system. Results are re-ranked, deduplicated and mixed, then an answer with citations is generated by whichever model you supply a key for. Everything lands in SQLite or Postgres for later analysis.

This repository is Swirl Community, the Apache 2.0 edition.

• Connectors: more than a hundred sources are supported, and the connector objects are built to be extended.
• Galaxy UI: the same interface that ships with the commercial edition.
• Re-ranking: cosine vector similarity using the spaCy large model and NLTK, plus duplicate detection and result mixers.
• Processors: a pipelined architecture transforms queries, responses and results as they pass through.
• Federation: synchronous or asynchronous, over a clean REST API.

Getting started is a compose file and one Docker command, roughly two minutes, arriving ready to search Arxiv, European PMC and Google News. That Docker setup keeps nothing when it shuts down, so follow the persistent install guide for real use. A paid enterprise edition adds a three-pass reranker, canonical answers and an MCP server for agents.